This invention concerns a process for multisensor equalization in a radioelectric receiver consisting of demodulating a digital message in the presence of multi-propagation paths and interfering sources, reducing the number of factors to be adapted necessary for the multisensor equalizer calculation, for modulations formed of frames comprising learning sequences and information symbol sequences. The invention also concerns a radioelectric receiver embodying such a process. The invention is based on antenna processing techniques, and therefore requires the use of a network comprising several sensors.
There are many fields of application of this invention, all concerning communications that need an equalizer to perform the single sensor demodulation, such as for example:
high throughput modulation (2400 bit/s, etc.) in the high frequency (HF) range, PA1 modulations of systems in the V/UHF range such as GSM, DECT, etc. PA1 in the HF range, multi-propagation paths output from reflections on the various ionospheric layers may be spaced by 5 ms, or several times the symbol duration in the case of modulations with a typical band width of 3 kHz. PA1 in the V/UHF range, for very high GSM type throughputs (270 kbit/s, giving a symbol duration of 3.7 .mu.s) in urban or mountainous environments, the various paths originating from reflections on various obstacles (buildings, mountains, etc.) may be separated by 10 or even 20 .mu.s. PA1 the sensors are identical and disposed at different points in space, discrimination between the useful signal and interference being effected according to the direction of arrival; PA1 the sensors are all disposed at the same point in space (colocalised antenna) and have different radiation diagrams. This means that discrimination can be carried out on the basis of polarisation and direction of arrival; PA1 the two configurations described above can be combined: several colocalised antennas can be disposed at different points in space. PA1 according to direction of arrival, PA1 according to modulation, PA1 according to time, for example, with frequency evasion links, PA1 according to power, PA1 blindly (for example, higher order source separation methods). PA1 it "aligns" on the direction of one of the paths, i.e. it phase realigns the contributions of this path on the various sensors (for omnidirectional sensors, a signal to noise ratio gain of 10 log N is obtained, where N is the number of sensors used), PA1 it also attempts to eliminate non-correlated paths from the signal, thus losing the energy associated with these paths. PA1 at least two sensors connected to a unit carrying out the preliminary processing and synchronisation of the receiver input signal, the outputs of this unit being connected respectively to a first series of inputs and a second series of inputs of the spatial part of the equaliser, the first series of inputs corresponding respectively to the inputs of the spatial filters relating to each of the paths selected from a determined number of paths detected, and the second series of inputs corresponding respectively to the inputs of a unit for the calculation of the input signals of the transverse part of the temporal part of the equaliser, and wherein the transverse part of the temporal part features a transverse filter of determined coefficients, the temporal part also featuring a recursive part consisting of a decision module whose output is connected to the input of a recursive filter of determined coefficients, the recursive filter being located in a loop and receiving on its input the sum of the output signals of the spatial part and of the transverse part, from which is subtracted the signal output by the recursive part.
For many applications in digital radio communication, transmission between the transmitter and the receiver takes place along several propagation paths:
Since the delay time for these various applications may exceed the symbol duration, equalization becomes necessary to compensate for the inter-symbol interference (IIS) thus generated. In many systems currently in service, adaptation to these propagation conditions is made possible by insertion of the known receiver learning sequence in the wave shape. Different solutions are then possible for adaptive equalization of the received useful signal.
The first two solutions described below concern single sensor equalization. Antenna filtering techniques described below use multisensors.
A first solution consists in using a Viterbi algorithm which requires a prior estimation of the propagation channel using the learning sequence. This equalisation method has the advantage of minimising the probability of error across the whole sequence of information symbols, but becomes very costly when the duration of the pulse response of the channel is much greater than the symbol duration. In fact, the number of states that the Viterbi algorithm must process is equal to M.sup.L, where M is the size of the modulation alphabet and L is the length of the pulse response of the channel expressed as a number of symbol periods. This solution is used for GSM type applications where the Viterbi algorithm typically consists of 32 states (L=5 and M=2).
In the HF band, the particular field of application of the invention, the number of states becomes too great for the Viterbi algorithm to be practically realisable (typically, M is 4 or 8, while L is equal to 12, which corresponds to a pulse response spread over 5 ms), and a second solution using a DFE equaliser is often used.
This second solution consists in using learning sequences as the response of an adaptive algorithm used to minimise a MQE (Mean Quadratic Error) criterion. This solution uses a "Decision Feedback Equaliser" (DFE).
Such an equaliser is intended to supply to a decision module adapted to the modulation in question a signal in which ISI has been eliminated or at least reduced to a great extent. To this end, the DFE equaliser uses transverse and recursive self-adapting filters which are adapted by a least squares type algorithm, preferred to a gradient algorithm for reasons of speed of convergence. The known symbols in the learning sequences are used for the adaptation of the different coefficients. The tracking of channel variations beyond the known sequences is effected using symbols which are selected (detemined) as responses as necessary during the execution of the process.
The single-sensor DFE equaliser can compensate for ISI caused by multiple propagation paths, but is not capable of phase realigning these different paths. Thus, in the presence of two stationary paths of the same amplitude, the DFE equaliser produces losses of approximately 3 dB with respect to a white Gaussian noise channel: it endeavours to retain the contribution of one of the paths and to eliminate the second using the recursive part.
Moreover, in the HF band the different propagation paths are very often affected by flat fading. Fading is a phenomenon linked to the variation of the multiple paths which in turn produces a variation of the received power, or even in extreme cases fading or dying out of the signal paths. When fading is strong, a DFE equaliser's performance is seriously reduced.
In addition, these techniques rapidly become inefficient in the presence of jamming, which means that it is necessary to use known specific anti-jamming techniques such as error correction encoding, elimination of jamming by notched filtering, use of frequency evasion links, etc. These techniques are used in many operational systems, but are nonetheless of limited effect when interference is strong and occupies the whole of the useful signal band. In such conditions, it is necessary to use more effective anti-jamming means based on the use of antenna filtering techniques.
Antenna filtering techniques appeared in the early 1960's. One in particular is described in an article of P. W. HOWELLS "Explorations in fixed and adaptive resolution at GE and SURC", IEEE Trans-Ant-Prop, vol. AP-24, no. 5, pp 575-584, Sept. 1976, while an exhaustive synthesis is presented in a doctorate thesis presented by P. CHEVALIER at the University of Paris sud in June 1991 entitled "Antenne adaptative: d'une structure lineaire a une structure non lineaire de Volterra" ("The adaptive antenna: from a linear structure to a non-linear Volterra structure"). These techniques are designed to combine the signals received by the various sensors making up the antenna so as to optimise its response to the useful signal and jamming scenario in question.
The selection of sensors and their disposition is an important parameter which has a central influence on the performance of the system. Three basic configurations are possible:
In addition, since propagation and jamming conditions can change over time, it is essential that the system be capable of adapting the antenna to these variations in real time through the use of a particular antenna filtering technique: the adaptive antenna. An adaptive antenna is one which detects and reacts to sources of interference automatically by constructing holes in its radiating diagram in their direction, while at the same time improving reception of the useful source, without any prior knowledge of the interference and on the basis of a minimal amount of information on the useful signal. Moreover, the tracking capabilities of the algorithms used make an adaptive antenna able to respond automatically to a changing environment.
Adaptive antennas are characterised by the way in which they discriminate between the useful signal and interference, i.e. by the nature of the information relating to the useful signal which they use. This discrimination process can be carried out in one of five different ways:
Up until very recently, transmission systems have always been based upon the independent operation of single-sensor adaptive equalisation and adaptive antenna techniques, which results in less than optimised performance.
Thus, the system described in an article by R. Dobson entitled "Adaptive antenna array", patent no. PCT/AU85/00157 of February 1986, which uses discrimination according to time, is efficient in terms of interference rejection, but makes no attempt to improve the useful signal to noise ratio.
In a transmission context, and when learning sequences are introduced into the wave form, it is preferable to use antenna processing techniques based on discrimination according to modulation, as these techniques enable optimisation of the useful signal to noise ratio. Most techniques used nowadays attribute complex weightings to each of the sensors of the adaptive antenna. Such an antenna is capable of rejecting interference, but in the presence of multiple propagation paths:
In order to improve the performance of this type of antenna processing in the presence of multiple propagation paths, it is possible to combine it with a single-sensor equalisation technique to obtain a multi-sensor equaliser consisting of a spatial part, composed of different filters disposed on each of the reception channels, and a temporal part located at the output of the spatial part. All the filters making up the spatial part and the temporal part are jointly adapted to the same error signal.
Several multi-sensor equalisers have already been proposed and studied, principally in the field of mobile radio transmissions, and these are particularly described in an article by K. E. Scott and S. T. Nichols entitled: "Antenna diversity with Multichannel Adaptive Equalization in Digital Radio" and in an article by P. Balaban and J. Salz entitled "Optimum Diversity Combining and Equalisation in Digital Data Transmission with Applications to Cellular Mobile Radio--Part 1: Theoretical Considerations", IEEE Trans. on Com., vol. 40, no. 5, pp 885-894, May 1992.
Up to now, such equalisers have been intended to combat the selective fading engendered by multiple paths in a non-jammed environment. They consist of Finite Pulse Response filters, one on each channel, followed by an adder then a monodimensional equaliser equalising at the symbol rate. The criterion used for the optimisation of these multi-sensor equalisers is the minimisation of MQE between their output and a response determined by the learning sequences.
In the equaliser proposed by Scott et al, coefficient adaptation is carried out by a least squares algorithm, and its use for a HF channel cannot be envisaged given the wave forms used. Taking into account the temporal spread of the multiple paths, the number of coefficients to be adapted is too great for the algorithm to be able to converge with the learning sequence.